A national survey of Iranian general population to estimate a value set for the EQ-5D-5L.

Objectives: The main aim of this study is to estimate a national value set of the EQ-5D-5L questionnaire for Iran.

Methods: The composite time trade-off (cTTO) and discrete choice experiment (DCE) methods; and the protocol for EuroQol Portable Valuation Technology (EQ-PVT) were used to estimate the Iran national value set. 1179 face-to-face computer-assisted interviews were conducted with adults that were recruited from five Iran major cities in 2021. Generalized least squares, Tobit, heteroskedastic, logit, and hybrid models were used to analyze the data and to identify the best fitting model.

Results: According to the logical consistency of the parameters, significance levels and prediction accuracy indices of the MAE; a heteroscedastic censored Tobit hybrid model combining cTTO and DCE responses was considered as the best fitting model to estimate the final value set. The predicted values ranged from - 1.19 for the worst health state (55555) to 1 for full health (11111), with 53.6% of the predicted values being negative. Mobility was the most influential dimension on health state preference values.

Conclusions: The present study estimated a national EQ-5D-5L value set for Iranian policy makers and researchers. The value set enables the EQ-5D-5L questionnaire to use to calculate QALYs to assist the priority setting and efficient allocation of limited healthcare resources.